🎬 Manim Animation Generator

An intelligent animation generation system that converts natural language descriptions into mathematical animations using Manim. The system consists of a Streamlit web interface powered by Azure OpenAI and a FastMCP server for animation rendering.

🏗️ Architecture

Streamlit App (Cloud) 
    ↓ (Natural Language)
Azure OpenAI API (Converts to Manim Code)
    ↓ (Manim Code)
FastMCP Server (Renders Animation)
    ↓ (Video)
Streamlit App (Displays Result)

📋 Prerequisites

• Python 3.9 or higher
• Azure OpenAI API key and endpoint
• FastMCP Cloud account (for deployment)
• GitHub account (for code hosting)

🚀 Quick Start - Local Testing

1. Install Dependencies

# Create virtual environment
python -m venv venv
venv\Scripts\activate  # Windows

# Install dependencies
pip install -r requirements-mcp.txt
pip install -r requirements-streamlit.txt

2. Configure Environment

Create .env file:

AZURE_OPENAI_API_KEY=your_api_key
AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com/
AZURE_OPENAI_DEPLOYMENT_NAME=your_deployment_name
AZURE_OPENAI_API_VERSION=2024-12-01-preview
MCP_SERVER_URL=http://localhost:8000

3. Run Locally

Terminal 1 - MCP Server:

python mcp_server.py

Terminal 2 - Streamlit App:

streamlit run streamlit_app.py

🌐 Cloud Deployment

Deploy to FastMCP Cloud

1. Push code to GitHub:

git push origin main

2. Go to FastMCP Cloud Dashboard: https://cloud.fastmcp.io

3. Create new deployment from GitHub repository

4. Get deployment URL (e.g., https://manim-mcp-server.fastmcp.io)

5. Update Streamlit Cloud secrets:

MCP_SERVER_URL = https://your-deployment-url.fastmcp.io

Deploy Streamlit App to Streamlit Cloud

1. Push code to GitHub

2. Go to https://share.streamlit.io

3. Connect your repository

4. Add secrets in deployment settings:

AZURE_OPENAI_API_KEY = your_key
AZURE_OPENAI_ENDPOINT = your_endpoint
AZURE_OPENAI_DEPLOYMENT_NAME = your_deployment
MCP_SERVER_URL = https://your-mcp-server-url.fastmcp.io

The app will open in your browser at http://localhost:8501

🌐 Deployment

📁 Project Structure

MCPproject/
├── streamlit_app.py              # Streamlit UI
├── mcp_server.py                 # MCP Server with FastAPI
├── requirements-mcp.txt          # MCP Server dependencies
├── requirements-streamlit.txt    # Streamlit dependencies
├── mcpconfig.json                # FastMCP configuration
├── .streamlit/
│   └── config.toml              # Streamlit settings
├── .gitignore                    # Git ignore (protects .env)
├── .env                          # Local secrets (not in git)
└── README.md                     # This file

🔑 Key Features

• Natural Language Input: Describe animations in plain English
• AI-Powered: Uses Azure OpenAI to convert text to Manim code
• Instant Rendering: FastMCP server generates videos quickly
• Web Interface: Clean Streamlit UI for easy interaction
• Cloud Ready: Deploy on Streamlit Cloud + FastMCP Cloud

📝 Usage Example

1. Open Streamlit app
2. Enter: "Create a circle that morphs into a square"
3. Click "Generate Animation"
4. View and download the generated video

🔐 Security

• .env file is gitignored (secrets never pushed to GitHub)
• Use Streamlit Cloud secrets for production
• Use FastMCP Cloud secrets for MCP server

🛠️ Environment Variables

# Azure OpenAI
AZURE_OPENAI_API_KEY        # Your API key
AZURE_OPENAI_ENDPOINT       # Your endpoint URL
AZURE_OPENAI_DEPLOYMENT_NAME # Deployment name
AZURE_OPENAI_API_VERSION    # API version (2024-12-01-preview)

# MCP Server
MCP_SERVER_URL              # URL of FastMCP server

📚 Documentation

• Manim: https://docs.manim.community/
• Streamlit: https://docs.streamlit.io/
• FastMCP: https://docs.fastmcp.io/
• Azure OpenAI: https://learn.microsoft.com/en-us/azure/ai-services/openai/

🚀 Deployment Links

• Streamlit Cloud: https://share.streamlit.io
• FastMCP Cloud: https://cloud.fastmcp.io
• GitHub: https://github.com/kavsrd13/ManimMCPServer

📧 Support

For issues:

• Check error logs in respective dashboards
• Review Manim documentation for animation syntax
• Verify API credentials are correct

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Built with Azure OpenAI + FastMCP + Manim + Streamlit 🎨